As platforms like AlphaSense automate the grunt work of research, the advantage is no longer in finding information. The new "alpha" for investors comes from asking better, more creative questions, identifying cross-industry trends, and being more adept at prompting the AI to uncover non-obvious connections.

AI's core strength is hyper-sophisticated pattern recognition. If your daily tasks—from filing insurance claims to diagnosing patients—can be broken down into a data set of repeatable patterns, AI can learn to perform them faster and more accurately than a human.

Historically, investment tech focused on speed. Modern AI, like AlphaGo, offers something new: inhuman intelligence that reveals novel insights and strategies humans miss. For investors, this means moving beyond automation to using AI as a tool for generating genuine alpha through superior inference.

AI's strength in pattern recognition could become its weakness in an adaptive market. Companies and human investors may learn to manipulate AI-driven funds by feeding them historical patterns that signal value, such as initiating dividends during distress to trigger buys, ultimately leading the AI to underperform.

Howard Marks believes AI's strength in pattern recognition is also its key limitation in investing. It can extrapolate from historical data but cannot identify true novelty, like a revolutionary business model or a visionary founder like Steve Jobs, where no pre-existing pattern exists. This preserves a role for unique human judgment.

When Ken Griffin saw AI replicate the work of his PhDs, his "depression" may have been less about job loss and more about strategy. He realized Citadel's core asset—an army of elite human analysts—could be commoditized by AI, eroding a key competitive advantage.

AI tools can now perform complex fundamental analysis, commoditizing a once-essential analyst skillset. This shift means that a deep understanding of market structure, positioning, and trading dynamics is becoming the more valuable and differentiating skill for portfolio managers seeking an edge.

AI tools are automating traditional analytical tasks, diminishing the edge from pure technical skill. The most valuable investors will be those who can apply superior judgment, market structure understanding, and pattern recognition to challenge and interpret AI-generated insights.

As AI masters the analysis of financial filings and transcripts, the source of investment alpha may shift to information that is difficult for models to process. Qualitative insights from attending conferences, judging a CEO's character via a handshake, or other forms of scuttlebutt could become increasingly valuable differentiators for human investors.